Self-Maintained Tablespace with Automatic Fullness-Based Partition Splitting
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Solution Overview
Problem
Existing database tablespaces require manual intervention by administrators to redistribute data when partitions become full, leading to labor costs and inefficiencies in maintenance.
Innovation Solution
A self-maintained tablespace that automatically splits into progeny partitions based on split percentage and ratio, determined by a machine learning model, to prevent fullness, optimizing performance without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual intervention is used to redistribute data when partitions become full, then database maintenance can be performed, but labor costs increase and maintenance efficiency decreases
Solution Approach 1:
The partitioning system automatically monitors partition fullness levels and triggers split operations without administrator intervention. The system self-manages the redistribution of data when partitions reach predefined fullness thresholds, eliminating the need for manual maintenance operations while improving maintenance efficiency.
Solution Approach 2:
The system pre-defines split percentage thresholds and split ratios in advance, so when a partition reaches a certain fullness level, the split operation is automatically triggered without requiring real-time human decision-making. This preliminary configuration enables automated response to partition fullness conditions.
2Loss of time
If partitions are manually reorganized, then fullness can be managed, but time is lost due to manual intervention
Solution Approach 1:
The system continuously monitors partition fullness and automatically executes split operations when thresholds are reached, eliminating the time administrators would spend manually assessing and reorganizing partitions. The automated monitoring and trigger mechanism ensures immediate response to fullness conditions without human delay.
Solution Approach 2:
The system implements continuous feedback monitoring of partition fullness levels, comparing current state against predefined thresholds. When the feedback indicates a partition has reached the split percentage, the system automatically triggers the split operation, creating a closed-loop control system that eliminates manual assessment time.
3Extent of automation
If automatic split is implemented, then maintenance automation is improved, but system complexity increases
Solution Approach 1:
The system pre-configures split percentages and split ratios during tablespace creation or modification. These preliminary settings establish the automation logic in advance, so the actual split operations simply follow predefined rules without requiring complex real-time decision-making algorithms, thereby limiting the increase in system complexity.
Solution Approach 2:
The automation is achieved by monitoring and responding to changes in partition fullness parameters. When the fullness parameter reaches the predefined split percentage threshold, the system triggers a split operation using the predefined split ratio. This parameter-based control approach simplifies the automation logic compared to more complex intelligent systems.
Data Source
AI summary
A system, method, and computer program product are configured to: provide a tablespace comprising an original partition having a lower boundary L, an upper boundary U, a split percentage P, and a split ratio R; and in response to the original partition reaching a fullness of P, automatically split the original partition to a first progeny partition and a second progeny partition, wherein the first progeny partition has a lower boundary L1 that is the same as the lower boundary L of the original partition and an upper boundary U1 that is determined based on whether the insert is a sequential or random insert, and wherein the second progeny partition has an upper boundaries U2 that is the same as the upper boundary U of the original partition and a lower boundary L2 that is determined based on whether the insert is a sequential or random insert.